The effects of structural and psychological empowerment on perceived respect in acute care nurses
Bibliographic record
Abstract
BACKGROUND: The recruitment and retention crisis has catalyzed interest in workplace empowerment for nurses. Many nurses feel that they do not receive the respect they deserve in hospital settings; however, there are few systematic studies of respect for nurses. OBJECTIVE: The purpose of this study was to examine the relationships between structural and psychological empowerment and their effects on hospital nurses' perceptions of respect. METHOD: A secondary analysis was conducted of data from a larger study of 500 randomly selected hospital staff nurses. A predictive, non-experimental survey design was used to test a hypothesized model derived from Kanter's Work Empowerment Theory. RESULTS: Both structural and psychological variables were significant independent predictors of respect, although structural empowerment had considerably greater explanatory power. CONCLUSIONS: The findings support Kanter's theory. Hospital nurses who perceive themselves to be structurally and psychologically empowered are more likely to feel respected in the workplace. IMPLICATIONS FOR NURSING MANAGEMENT: Changing workplace structures is within the mandate of nurse managers in their roles as advocates for and facilitators of high-quality care. Nurse managers have the influence and resources to facilitate empowering work conditions that can increase nurses' feelings of being respected. In addition, promoting collaborative inter-professional and intra-professional relationships and assuring continuous support to nurses are particularly important strategies for building respect.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".